2023-05-18 カリフォルニア大学サンディエゴ校(UCSD)
◆機械学習を用いて、人間とハエの遺伝子活性化要素を比較し、人間特有のDNA配列を同定しました。この研究は、バイオテクノロジーや医学において有用な合成DNA配列の同定に応用できる可能性を示しています。AI技術は生物学の分野でますます重要な役割を果たすことが期待されています。
<関連情報>
- https://today.ucsd.edu/story/artificial-intelligence-catalyzes-gene-activation-research-and-uncovers-rare-dna-sequences
- https://genesdev.cshlp.org/content/early/2023/04/25/gad.350572.123.abstract
ショウジョウバエとヒトのDPRエレメントを解析した結果、機械学習で特異性を高めることができるヒトの特異的な変異体が明らかになった Analysis of the Drosophila and human DPR elements reveals a distinct human variant whose specificity can be enhanced by machine learning
Long Vo ngoc,Torrey E. Rhyne and James T. Kadonaga
Genes & Development Published:April 25, 2023
DOI:doi:10.1101/gad.350572.123
Abstract
The RNA polymerase II core promoter is the site of convergence of the signals that lead to the initiation of transcription. Here, we performed a comparative analysis of the downstream core promoter region (DPR) in Drosophila and humans by using machine learning. These studies revealed a distinct human-specific version of the DPR and led to the use of machine learning models for the identification of synthetic extreme DPR motifs with specificity for human transcription factors relative to Drosophila factors and vice versa. More generally, machine learning models could similarly be used to design synthetic DNA elements with customized functional properties.
